Geospatial Analysis and Social Media Information Analysis Techniques

Review on Different Techniques Used for Geospatial Analysis and Social Media Information Analysis

This assessment is designed to demonstrate a student’s completion of the following Learning Outcomes:

• Demonstrate an understanding of concepts underlying geospatial analysis and apply them on real life data.

• Carry out social analytics in combination with geospatial data, applying appropriate techniques on social information.

• Design, prototype and implement geospatial applications.

• Identify and describe emerging technologies and research areas relevant to geospatial analytics.

Review on different techniques used for geospatial analysis and social media information analysis

A detailed review on the following applications

- ArcGIS

- Open Street Map

- Google Earth

- Google Fusion Table

- Twitter

Your review should cover following aspects of each application

- Brief introduction

- Functionality

- Common use in different areas (business, social study, public health etc.)

- Strengths and limitations

1.2 Report on the importance of geospatial analysis in different areas (excluding social media) and how these areas are benefiting from geospatial analysis.

Choose any THREE areas from the following link (http://www.esri.com/industries), and write a report, explaining current state, what are the challenges, what solutions are available, future direction. (N.B. you are not limited to esri’s applications/areas)

2.1 Apply geospatial visualization application (e.g. ArcGIS, Google Map, Google Fusion Table) on the dataset provided Use the dataset of Age distribution of population by gender and local authority with aforementioned applications (any ONE application). Utilize appropriate visualization techniques (e.g. different markers, heatmap etc.) from the application of your choice to map population density of different age groups (male female combined) of different local

authorities of Wales in year 2017. With screen shots, create a dashboard and provide a brief description of your interpretation of each screen shot.

2.2 Analyse the dataset and answer specific questions with Python scripts.

• Plot population distribution of all areas for the year 2016.

• Which age group has highest and lowest distribution in year 2017 and where?

• Map population density (male female combined) change over 2001 – 2017 for the age group 30-44 years.

• Identify and map top three areas with highest number of population growth for the aforementioned age group and years.

• Identify and map highest and lowest female distribution in year 2016 across all age groups and areas.

2.3 Sentiment analysis on Twitter